RNA-seq analysis reveals differentially expressed inflammatory chemokines in a rat retinal degeneration model induced by sodium iodate

Abstract

Objective

Retinal degeneration (RD) is a group of serious blinding eye diseases characterized by photoreceptor cell apoptosis and progressive degeneration of retinal neurons. However, the underlying mechanism of its pathogenesis remains unclear.

Methods

In this study, retinal tissues from sodium iodate (NaIO₃)-induced RD and control rats were collected for transcriptome analysis using RNA-sequencing (RNA-seq). Analysis of white blood cell-related parameters was conducted in patients with retinitis pigmentosa (RP) and age-related cataract (ARC) patients.

Results

In total, 334 mRNAs, 77 long non-coding RNAs (lncRNAs), and 20 other RNA types were identified as differentially expressed in the retinas of NaIO₃-induced RD rats. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that differentially expressed mRNAs were mainly enriched in signaling pathways related to immune inflammation. Moreover, we found that the neutrophil-to-lymphocyte ratio was significantly higher in RP patients than in ARC patients.

Conclusion

Overall, this study suggests that multiple chemokines participating in systemic inflammation may contribute to RD pathogenesis.

Keywords

Retinal degeneration sodium iodate RNA-seq rat model inflammation chemokine routine hematology analysis

Introduction

Retinal degeneration (RD) is a kind of blinding disease caused by various factors, including heredity, light damage, and aging. The progressive breakdown and loss of photoreceptor cells and retinal pigment epithelial (RPE) cells is involved in this disease.^1–3 RD includes age-related macular degeneration (AMD), retinitis pigmentosa (RP), and other conditions caused by RPE/photoreceptor degeneration.⁴ AMD is a chronic neurodegenerative disease, affecting 10% of people over 65 years old and more than 25% of people over 75 years old.⁵ With the continued aging of the global population, the prevalence of AMD is expected to increase significantly. By 2040, about 288 million people worldwide may suffer from AMD.⁶ RP is a clinically and genetically heterogeneous group of retinal disorders, the global prevalence of which is approximately 1 in 4000.⁷ Increased infiltration of circulating macrophages and activation of resident microglia have been observed in both inherited and acquired forms of RP.⁸ In recent years, many studies have focused on finding effective treatment methods for RD. Current treatment measures include gene therapy and stem cell transplantation, among others.⁹ However, effective treatment methods for this disease are still lacking because of the complexity of the pathogenic factors involved.

Animal models are considered useful tools for studying RD, but phenotypic inconsistencies and penetrance caused by genetic heterogeneity complicate the standardization of test parameters.¹⁰ Therefore, the use of a standardized chemical induction model is required for investigating RD pathogenesis. The sodium iodate (NaIO₃) model is widely used to simulate the effects of AMD and RP because NaIO₃ is an antimetabolite. When injected systemically, it accumulates in the retina and causes oxidative stress, leading to RPE cell necrosis and the death of photoreceptors as secondary damage.^11,12 This can result in loss of vision. The NaIO₃ model has been successfully used in many species, including rats,¹² mice,¹³ and pigs,¹⁴ furthering our understanding of RD pathogenesis. In this study, we used the NaIO₃-induced RD model in rats and analyzed the differential transcriptomes by RNA-sequencing (RNA-seq). This enabled us to further investigate RD pathogenesis and provide a basis and reference for subsequent clinical diagnosis and treatment.

Methods

Animals

All animal experiments were performed in accordance with the Association for Research in Vision and Ophthalmology (ARVO) statement for the Use of Animals in Ophthalmic and Vision Research and approved by the Animal Care and Use Committee of Jinan University (Approval No. IACUC-2020-07-0016). Eighteen male Sprague–Dawley rats aged 6 to 8 weeks were used in this study. The animals were purchased from the Guangdong Medical Experimental Animal Center (Guangzhou, China). Rats were housed in a controlled environment at 22 ± 2°C and relative humidity of 55 ± 10% under a photoperiod of 12 hours. Rats were allowed access to standard lab chow and autoclaved tap water ad libitum.

Patients and data collection

Patients who underwent age-related cataract (ARC) surgery from 2017 to 2019 in Shenzhen Eye Hospital were screened according to inpatient medical records, and the clinical manifestations were blurred vision and lens opacity. Simultaneously, age- and sex-matched patients with primary RP were screened, and the main clinical manifestations were progressive visual field loss, night blindness, and abnormal electroretinogram. Patients with other ocular diseases and history of ocular trauma, systemic diseases (such as hypertension, diabetes, and chronic inflammatory diseases), smoking, and long-term medication were excluded. All participants fasted one day before blood collection, and whole blood analysis was performed in the laboratory using Mindray BC-6800 automatic hematology analyzers (Mindray, Shenzhen, China). All participants provided written informed consent before the start of the study. The study protocol was approved by the ethics committee of Shenzhen Eye Hospital (Approval No. 2022KYPJ028), and the study was performed according to the Declaration of Helsinki.

Animal treatment and sample collection

Rats in the experimental group (n = 9) were intraperitoneally injected with 50 mg/kg NaIO₃ diluted in phosphate-buffered saline (PBS) (Sigma-Aldrich, St. Louis, MO, USA) (NaIO₃-treated group), while the control rats (n = 9) were injected with the same volume of PBS. At 10 days post-injection, the eyeballs were collected in ice-cold PBS for ocular dissection. Retina samples from the right eyes were collected in ice-cold PBS under a dissecting microscope and placed in ice-cold TRIzol (Sigma-Aldrich) for RNA-seq and quantitative reverse transcriptase PCR (qRT-PCR) validation. The retina samples from the left eyes were used for histological studies.

Histological study

Nine retinal samples from each group were fixed in 4% paraformaldehyde, embedded in paraffin, and sectioned at a thickness of 4 to 6 µm. Slides were stained with hematoxylin and eosin (H&E; Sigma-Aldrich).

RNA-seq

Total RNA from the retina tissue was isolated using TRIzol (Thermo Fisher Scientific, Waltham, MA, USA) following the manufacturer’s instructions. RNA quality was examined using the ND-1000 Nanodrop (Thermo Fisher Scientific) at 260/280 nm and 260/230 nm. RNA integrity was assessed using the Agilent 2200 Tape Station (Agilent Technologies, Santa Clara, CA, USA). Ribosomal RNAs (rRNAs) were removed using the EpicentreRibo-Zero rRNA Removal kit (Illumina, San Diego, CA, USA) and fragmented to roughly 200 bp. Purified RNA samples were used for first-and second-strand cDNA synthesis using the NEBNext Ultra™ RNA Library Prep kit for Illumina (New England Biolabs, Ipswich, MA, USA). The purified library was re-evaluated using the Agilent 2200 Tape Station and Qubit 2.0 (Life Technologies, Carlsbad, CA, USA). The samples were then diluted to 10 pM for cluster generation and sequencing using the HiSeq3000 Sequencing System (Illumina). The raw data were submitted to the National Center for Biotechnology Information Sequence Read Archive (NCBI SRA) (accession number: PRJNA735022).

Reference genome mapping

Clean data were obtained after filtering out spliced sequences and low-quality reads from the raw data. Then, clean reads were mapped to the rat reference genome using HISAT2.¹⁵

Analysis of differentially expressed genes (DEGs)

The expected number of reads per kilobase of transcript sequence per million base pairs sequenced was used to estimate gene expression levels. DEGs were determined by DEseq using read counts as the input sources, followed by the Benjamini–Hochberg multiple test correction method.¹⁶ |Log2 fold change| >1.0 and a q-value <0.05 were used to identify DEGs and generate a heat map. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using KOBAS 3.0.¹⁷

Principal component analysis (PCA)

PCA was performed to obtain an overview of the gene expression profile using OmicShare tools (www.omicshare.com/tools).

Protein-protein interaction (PPI) network construction

The PPI network of DEGs was created using STRING (http://string.embl.de/) and visualized using MCODE in Cytoscape 3.5.3. Nodes in biological networks were analyzed using CytoHubba in Cytoscape.

qRT-PCR

Total RNA from the retinal tissue of a separate NaIO₃-treated group was obtained using TRIzol and reverse transcribed into cDNA using the PrimeScript RT Reagent kit (Takara Biotechnology, Dalian, China). qRT-PCR was performed using the SYBR™ Green PCR Master kit (Thermo Fisher Scientific) on the Step-OnePlusTM Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) following the manufacturer’s instructions. Each sample was tested in triplicate, and the housekeeping genes GAPDH, ACTB, and EEF2 were used to normalize the mRNA levels using the 2^−ΔΔCt method. The primers used in this study are listed in Table S1.

Statistical analysis

The H&E staining experiment and qRT-PCR experiments were repeated independently in triplicate, and each independent test was performed with three biological replicates. SPSS 26.0 software (IBM, Armonk, NY, USA) was used for statistical analysis. The analysis method was selected according to whether the data were normally distributed: if so, the independent samples t-test was used for parametric analysis and data were expressed as mean ± standard deviation; if not, the Mann–Whitney U test was used for parametric analysis and data were expressed as median ± interquartile range. Statistical significance was set at P < 0.05. In addition, the Pearson correlation coefficient was calculated using SPSS to assess the correlation between the RNA-seq and qRT-PCR results.

Results

RD in NaIO3-treated rats

Rat retinal tissues were assessed using H&E staining for RPE damage (Figure 1). The retinas obtained from the control group were characterized by well-organized and clearly defined layers, including the retinal ganglion cell layer, inner plexiform layer, inner nuclear layer, outer plexiform layer, outer nuclear layer, layers of rods and cones, and retinal pigment epithelium (Figure 1a). In contrast, the retinas of rats treated with NaIO₃ showed a disrupted retinal pigment epithelial layer that had disappeared. The layer of rods and cones was also degenerated and extended toward the inner layer of the retina. This resulted in structural disorder of both the inner and outer nuclear layers, as well as thinning of the outer nuclear layer (Figure 1b).

Figure 1.

Hematoxylin and eosin (H&E) staining of rat retina tissues. (a) Control rats; the control group was administered a phosphate-buffered saline (PBS) solution for 10 days and showed intact histological structure of the retina and (b) Sodium iodate (NaIO₃)-treated rats; the NaIO₃ treatment group was administered 50 mg/kg NaIO₃ for 10 days and showed disruption of the retinal pigment epithelium (RPE) layer, degeneration of the layer of rods and cones, and extension into the inner layer of retina. The outer nuclear layer was thinner in the NaIO₃-treated group than in the control group. The scale bars denote 200 μm. N = 9 per group.

Identification of DEGs

PCA indicated that rats in the NaIO₃-treated and control groups showed sufficient dimensionality and variability (Figure 2a). In total, 431 genes were differentially expressed in the NaIO₃-treated group, of which approximately 90% were upregulated (Figure 2b/c and Table S2). RNA-seq data were submitted to NCBI SRA (accession number: PRJNA735022).

Figure 2.

Enrichment analysis of differentially expressed genes (DEGs) between NaIO₃-treated rat retinas (T) and the control group^©. (a) Principal component analysis of the DEGs. (b) Volcano plot for the DEGs. (c) Heat map of the DEGs, (d) Gene Ontology (GO) enrichment analysis of the DEG^© and (e) Kyoto Encyclopedia of Gene and Genomes (KEGG) pathway enrichment analysis of the DEGs.

Functional enrichment analysis of DEGs

GO enrichment analysis showed that DEGs in the NaIO₃-treated group were mainly involved in biological processes, such as leukocyte-mediated immunity and regulation of phagocytosis; cellular components, such as membrane region and extracellular matrix; and molecular functions, such as immunoglobulin receptor activity and complement binding (Figure 2d). In turn, KEGG pathway enrichment analysis indicated that DEGs were primarily involved in complement and coagulation cascades, the tumor necrosis factor (TNF) signaling pathway, and the chemokine signaling pathway (Figure 2e).

PPI network and module analysis

The PPI network was constructed using the proteins encoded by all DEGs, and two of the most significantly enriched modules were analyzed (Figure 3a/b). Module 1 was composed of 26 nodes and 173 edges, while module 2 was composed of 35 nodes and 114 edges. The top 20 hub genes and their corresponding node degrees are shown in Figure 3c.

Figure 3.

Protein–protein interaction (PPI) network analysis. (a–b) Top two modules identified by MCODE in Cytos^©e and (c) Top 20 hub genes and their corresponding degrees identified by CytoHubba in Cytoscape. All interaction networks were constructed with proteins encoded by differentially expressed genes in the present study.

Validation of DEGs

The expression levels of seven selected protein-coding genes (BCL3, CCL2, CXCL10, ICAM1, MMP3, SOCS3, and TNFRSF1A) that participate in immune responses and cell death, along with three randomly selected long non-coding RNAs (lncRNAs) (LOC102557376, H19, and LOC102554891), were validated using qRT-PCR. The results showed that compared with the control group, the expression levels of BCL3, CCL2, CXCL10, ICAM1, MMP3, SOCS3, TNFRSF1A, LOC102557376, and H19 were significantly increased in the NaIO₃-treated group while the LOC102554891 expression levels were significantly decreased in the NaIO₃-treated group. These qRT-PCR findings were in accordance with the RNA-seq data (Figure 4a/b). The log2 fold change (NaIO₃-treated vs. control) results obtained from qRT-PCR had a strong correlation (R² = 0.7201; P = 0.001) with the RNA-seq results, indicating the reliability of the RNA-seq analysis (Figure 4c).

Figure 4.

Validation of differentially expressed genes (DEGs) by quantitative reverse transcriptase PCR (qRT-PCR). (a) Expression of ten selected genes measured by RNA-seq; n = 3 per group. (b) Validation of DEG expression levels by qRT-PCR; n = 6 per group and (c) Correlation between RNA-seq and qRT-PCR data. Data are represented as means ± standard deviation, where P values were obtained through the Student’s t-tests. *, **, and *** indicate significant differences at P < 0.05, P < 0.01, and P < 0.001, respectively.

Blood component characteristics of RP and ARC patients

The ARC and RP groups each had 59 patients. There were no statistical differences in age and sex between the two groups (P > 0.05, Table 1). In the white blood cell-related parameters, the average percentage of neutrophils in the RP group was significantly higher than that in the ARC group (P < 0.05, Table 1), and the average percentage of lymphocytes in the RP group was significantly lower than that in the ARC group (P < 0.05, Table 1). The ratio of neutrophils to lymphocytes was significantly higher in RP patients than in ARC patients (P < 0.05, Table 1). Moreover, the percentage of basophils was also significantly different between the RP and ARC groups (P < 0.05, Table 1).

Table 1.

Analysis of white blood cell-related parameters in the retinitis pigmentosa (RP) and age-related cataract (ARC) patients.

	RP (n = 59 eyes)	ARC (n = 59 eyes)	P-value
Sex (males/females)^†	29/30	33/26	0.5804
Age (years)^†	46 ± 35	50 ± 31	0.8521
White blood cells (%)^§	6.51 ± 1.38	6.19 ± 1.39	0.2108
Neutrophils (%)^§	61.47 ± 6.88	58.71 ± 7.76	0.0427*
Lymphocytes (%)^§	30.03 ± 6.56	32.87 ± 7.08	0.0256*
Monocytes (%)^§	5.52 ± 1.33	5.75 ± 1.49	0.3831
Basophils (%)^†	0.50 ± 0.40	0.40 ± 0.30	0.1419
Eosinophils (%)^†	2.60 ± 1.00	1.70 ± 1.10	0.1061
Neutrophils (10⁹/L)^†	3.90 ± 3.30	3.70 ± 2.90	0.0975
Lymphocytes (10⁹/L)^†	1.80 ± 1.50	2.00 ± 1.60	0.3695
Monocytes (10⁹/L)^†	0.35 ± 0.30	0.34 ± 0.26	0.7459
Basophils (10⁹/L)^†	0.03 ± 0.02	0.03 ± 0.02	0.024*
Eosinophils (10⁹/L)^†	0.17 ± 0.06	0.09 ± 0.05	0.0604
Ratio of neutrophil/lymphocyte^†	2.05 ± 1.60	1.79 ± 1.37	0.0346*

^§P-value calculated using Student’s t-test, and the data are expressed as mean ± standard deviation. ^†P-value calculated using Mann–Whitney U test, and the data are expressed as median ± quarter spacing. *P < 0.05.

Discussion

RD is a blinding ophthalmic disease with common pathological characteristics that include photoreceptor degeneration and progressive vision loss.¹⁸ NaIO₃ is a chemical that can reliably induce damage to the RPE of rodents.¹² In the present study, we used NaIO₃ to induce RD in rats to explore the key mediators in the pathogenesis of this disease.

Compared with the control group, we identified 431 DEGs in the retinas of NaIO₃-treated rats that are involved in numerous biological processes and signaling pathways, including leukocyte proliferation regulation and the chemokine signaling pathway. Chemokines regulate the migration of leukocytes from blood to tissues, recruiting host defense cells to the site of infection. In this study, we found that the percentage of neutrophils, the number of basophils, and the ratio of neutrophils to lymphocytes in RP patients were significantly higher than those in ARC patients. Additionally, the percentage of lymphocytes was significantly lower in RP patients than in ARC patients. Neutrophils and lymphocytes are involved in retinal homeostasis and inflammation through immune responses.^19,20 One study found that circulating immune complexes are present in the serum of RP patients that can cause immune system disorders, deposit in retinal tissue, activate complement, and release inflammatory mediators, thereby causing an inflammatory response in the retinal tissue.²¹ Consistent with our results, previous work has shown that patients with ARC complicated by RP have significantly higher neutrophil-to-lymphocyte ratios than patients with ARC.¹⁹ In conclusion, the large number of differentially expressed chemokines in the RD model and the blood characteristics of RP patients in this study all suggest that the occurrence of RP is related to the systemic inflammatory response.

RD is a chronic inflammatory retinal degenerative disease associated with a chemokine-mediated inflammatory response.²² In the present study, the DEGs, such as CCL2, CXCL10, and CX3CR1, were substantially enriched in the immune response. CCL2 is the best-known CC chemokine and a key chemokine for regulating the migration and infiltration of monocyte-derived macrophages.²³ CCL2 is upregulated in rd10 RP mice, and co-knockout of the CCR2 gene, which encodes the CCL2 receptor CCR2, in rd10 mice increases the severity of RP, indicating the pathogenic roles of the CCL2-CCR2 axis in RP.²⁴ CXCL10 participates in RPE damage induced by 1000 lux light in rats and various autoimmune diseases that induce leukocyte chemotaxis to inflammatory sites.²⁵ Furthermore, the microglial response to chemokines is a marker of inflammation in RD. Overactivated microglia will release many pro-inflammatory factors to deteriorate the retinal microenvironment and aggravate the apoptosis of photoreceptor cells and retinal ganglion cells.²⁶

Furthermore, the expression and activation of the complement system are also involved in immunoregulation, leading to neurodegenerative diseases.²⁷ In the retina, multiple complement-related gene polymorphisms are associated with the genetic risk of AMD.²⁸ In both RP and AMD, microglia in the photoreceptor layer of the outer retina are relatively high in number, which is possibly the source of complement regulatory factors.²⁹ Here, we found that the expression levels of complement system-related genes, such as C5ar1, C3ar1, C4a, C4b, C1qb, and C1qc, were increased in RD rats. These results were consistent with those reported in previous studies.¹³ Silverman et al.³⁰ indicated that genetic depletion of C3 or CR3 (a receptor for C3b) increases microglial neurotoxicity to photoreceptors, indicating a proactive role of C3 activation. Therefore, the complement system may play an essential role in RD pathogenesis as a compensatory mechanism. However, further investigation is needed to confirm this speculation.

As an inflammatory cytokine with multiple biological activities, TNF plays an important role in retinal neurodegenerative diseases, such as RD, after binding to its receptor.³¹ In our study, the expression levels of TNF receptor superfamily member 1A (TNFRSF1A) and TNF receptor superfamily member 9 (TNFRSF9) were higher in the NaIO₃-treated group than the control group. TNFRSF1A is upregulated in canine models of photoreceptor degeneration, while the binding of TNF to its receptor induces apoptosis in retinal ganglion cells.³² Moreover, TNFα regulates the activity of ion channels and increases the release of glutamate, which can directly damage retinal ganglion cells.³³ As the main medium of cell adhesion and chemotaxis, TNFα induces the upregulation of intercellular adhesion molecule (ICAM-1) in the human retinal endothelium.³⁴ ICAM-1 can promote leukocyte adhesion to the retinal vascular system, activating cytokines and initiating inflammation.³⁵ The expression levels of ICAM1 were higher in the NaIO₃-treated group than in the control group in this study, which was consistent with a previous report that showed that the decrease in ICAM-1 expression can alleviate retinal injury mediated by leukocyte recruitment.³⁶ Therefore, inhibition of TNFα may be a potential new method to treat retinal neurodegenerative diseases, such as RD.

In addition, our results revealed that 77 lncRNAs were differentially expressed in the NaIO₃-treated group, including H19, an important imprinted gene. LncRNA H19 could initiate microglial pyroptosis and neuronal death in retinal ischemia/reperfusion injury.³⁷ A previous study reported that H19 expression was significantly increased in patients with wet AMD and in a choroidal neovascularization mouse model, and inhibiting H19 can inhibit M2 macrophage gene expression in this mouse model.³⁸ In addition, H19 participates in the regulation of epidermal mesenchymal transition in diabetic retinopathy.³⁹ Therefore, lncRNA H19 might be closely related to the occurrence of RD. However, the underlying regulatory mechanism needs to be studied further.

Overall, we constructed a rat model of RD by NaIO₃ treatment and found that the differentially expressed mRNAs were mainly involved in immune-inflammatory responses. In addition, combined with the blood characteristics of RP patients, we considered that systemic inflammation may play a role in the pathogenesis of this disease. However, our study has several limitations: 1) our sample size for the analysis of blood characteristics of RP patients is relatively limited; 2) because this is a retrospective study, other systemic immune inflammatory symptoms of patients are lacking. Therefore, it is necessary to comprehensively collect the systemic inflammatory characteristics of RP patients and collect more data on the blood components of these individuals. Next, we plan to isolate immune cells (microglia/macrophages) from NaIO₃-treated mouse retinas to explore the specific molecular mechanism of the immune response involved in RD.

Supplemental Material

sj-pdf-1-imr-10.1177_03000605221119376 - Supplemental material for RNA-seq analysis reveals differentially expressed inflammatory chemokines in a rat retinal degeneration model induced by sodium iodate

Supplemental material, sj-pdf-1-imr-10.1177_03000605221119376 for RNA-seq analysis reveals differentially expressed inflammatory chemokines in a rat retinal degeneration model induced by sodium iodate by Sheng Chen, Guo Liu, Xin Liu, Yun Wang, Fen He, Danyao Nie, Xinhua Liu and Xuyang Liu in Journal of International Medical Research

Footnotes

Author contributions

Xuyang Liu, SC, and GL designed the study. SC, GL, YW, and FH performed the experiments. Xinhua Liu and Xin Liu conducted bioinformatic analysis and wrote the manuscript. DN, Xinhua Liu, and Xuyang Liu revised the manuscript.

Data availability statement

RNA-seq data were submitted to NCBI SRA (accession number: PRJNA735022).

Declaration of conflicting interest

The authors declare that there is no conflict of interest.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by grants from the National Natural Science Foundation of China (NSFC grant 82070963), the Science and Technology Program of Shenzhen (JCYJ20180228164300106) and the Shenzhen San Ming Project (SZSM201812091).

ORCID iD

Sheng Chen

Supplemental material

Table S1. Primer sequences used for quantitative reverse transcriptase PCR validation.

Table S2. List of differentially expressed genes in the retinas of NaIO₃-treated rats versus control rats.

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Supplementary Material

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